Real Estate Prices Availability, Importance, and New ......2014/11/18 · Second IMF Statistical Forum 2014 (IMF, Washington DC, US) 2014/11/18 page. 1. Macroeconomic Policy and Housing

Second IMF Statistical Forum 2014 (IMF, Washington DC, US)

2014/11/18 page. 1 1

Second IMF Statistical Forum,

Statistics for Policymaking Identifying Macroeconomic and Financial Vulnerabilities

Session IV, Real Estate Prices—Availability, Importance, and New Developments

Discussion of Robert Shiller (Yale University) & Mick Silver (IMF)

Chihiro SHIMIZU [email protected]

Chihiro Shimizu

(Reitaku University & University of British Columbia)

November 18, 2014

Real Estate Prices—Availability, Importance, and

New Developments

Japanese experience and New challenge


2014/11/18 page.

1. Macroeconomic Policy and Housing Market

• Fluctuations in real estate prices and economic activities.

• In Japan, a sharp rise in real estate prices during the latter half

of the 1980s and its decline in the early 1990s has led to a

decade-long stagnation of the Japanese economy.

• Shimizu,C and T.Watanabe(2010), “Housing Bubble in Japan

and the United States,” Public Policy Review Vol.6, No.3,

431-472.

• At the center of my definition of the bubble are the epidemic

spread, the emotions of investors, and the nature of the news

and information media. Bubbles are not, in my mind, about

craziness of investors. (Robert Shiller (2014))

2 Chihiro SHIMIZU [email protected]


2014/11/18 page.

Official Statistics on Housing market: Rent and Prices.

• The most important link between asset prices

and goods & services prices is the one through

housing rents (Goodhart 2001)

• Fundamental Value: Expected Present Value

Models and Excess Volatility. Robert Shiller

(1984, 1989).

• Housing rents account for more than one

fourth of personal spending

1.0

1.5

2.0

2.5

3.0

3.5

QT

19

86

/1

QT

19

88

/1

QT

19

90

/1

QT

19

92

/1

QT

19

94

/1

QT

19

96

/1

QT

19

98

/1

QT

20

00

/1

QT

20

02

/1

QT

20

04

/1

QT

20

06

/1

CPI rent

Selling price index

3

Expenditures for housing services: 26.4% Housing rents: 4.9%

Imputed rents from owner occupied housing: 19.4%

Housing maintenance and others: 2.3%

“Consumer Price Index (CPI) in Tokyo, 2010”



2014/11/18 page. 4

Pr( 0) 1 Pr( 1) Pr( 1)

Pr( 0 | 1)Pr( 1)

Pr( 0 | 1)Pr( 1)

it

it

N

it

R

it

R R

it

N N

it i

it

t

it

I

I I

R

R

I

IR I

1 ititit RRR

Frequency of Rent Adjustments

0

5

10

15

20

25

30

35

26-S

ep-8

8

23-J

un

-91

19-M

ar-9

4

13-D

ec-96

9-S

ep-9

9

5-J

un

-02

1-M

ar-0

5

26-N

ov-0

7

10 t

hou

san

d y

en p

er m

on

th

Unit 11

Unit 219

Unit 220

Unit 245

Unit 298

Unit 308

Unit 339


Price Change

Probability of event on New Contract (IN)

and Renewed Contract (IR)

5

Negative Zero Positive Number of Observations

Turnover Units 85 397 44 526

(0.162) (0.755) (0.084) (1.000)

Rollover Units 18 576 0 594

(0.030) (0.970) (0.000) (1.000)

All Units 103 15,492 44 15,639

(0.007) (0.990) (0.003) (1.000)

Frequency of Rent Adjustments: Shimizu,

Nishimura and Watanabe (2010)

Fraction of housing units without no rent change per year

US 29%

Germany 78%

Japan 90%

Estimated by Genesove (2003)

Estimated by Kurz-Kim (2006)

Estimated by Shimizu et al (2010)


2014/11/18 page.

2. How should different countries construct Residential

property price indexes?

• The Eurostat published Handbook on Residential Property

Price indexes. Mick Silver (2014).

• The housing rent in CPI did not work well as a “mirror” of

housing prices.

• How should different countries construct residential property

price indexes?

• With the start of the RPPI Handbook project, the government

of Japan set up an Advisory Board in 2012 and is proceeding

with the development of a new transaction based

residential property price index (RPPI).

• Japan had only official appraisal based RPPI.



2014/11/18 page.

Transaction price-based index and

Appraisal value based index in Tokyo.

7

0

2

4

6

8

10

12

14

16

18

19

75

19

76

19

77

19

78

19

79

19

80

19

81

19

82

19

83

19

84

19

85

19

86

19

87

19

88

19

89

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

-60

-40

-20

0

20

40

60

80

100

120

MarketPrice

PublishedLandPrice

MarketPrice

PublishedLandPrice

In

dex:1975=

1

Calendar Year

an

nu

al c

han

ge r

ate (

%)

0

20

40

60

80

100

120

197509

197609

197709

197809

197909

198009

198109

198209

198309

198409

198509

198609

198709

198809

198909

199009

199109

199209

199309

199409

199509

199609

199709

199809

-40

-30

-20

-10

0

10

20

30

40

50

ULPI

MarketPrice

ULPI

MarketPrice

In

dex:1990M

arch

=100

Calendar Year/ Half yearly

an

nu

al c

han

ge r

ate (

%)


Lagging Problem

Appraisal

Error

Appraisal

Error


2014/11/18 page.

Estimation Methods for Constructing Residential

Property Price Indexes

• Housing: The location, history and facilities of each house

are different from each other in varying degrees.

• Houses have “particularity with few equivalents.”

• Quality-Adjustment Methodology in House Price Index

• → Hedonic method and Repeat sales method



2014/11/18 page.

Heteroskedasticity and Age Adjustments to the

Repeat Sales Index

• Case-Shiller adjustment:

• Case and Shiller (1987, 1989) have proposed a model in which

a GLS estimation is performed taking account of

heteroscedasticity.

• Age-adjustment to repeat sales index:

• The number of years for which are houses in the market is

remarkably short, the depreciation problem is potentially

significant in Japan.

• To take account of the age effect, we estimate Age-adjustment

to repeat sales index.(Shimizu, Nishimura and Watanabe(2010),

Wong, Chau and Shimizu(2013)).



2014/11/18 page.

Case of Japanese RPPI: Methods

• The question of which method is “best” remains open but the

depreciation bias in the standard repeat sales method tends to

lead us to prefer hedonic methods. (Handbook on

Residential Property Price indexes by EuroStat (2013))

• The government of Japan decided to prepare an official

residential property price index based on the hedonic method.

• In particular, it has been determined that it will be estimated

with the rolling window hedonic method proposed by

Shimizu, Takatsugi, Ono and Nishimura (1998) and Shimizu,

Nishimura and Watanabe (2010) and system development is

underway.



2014/11/18 page.

When did the condominium price hit bottom?

11

-0.16

-0.14

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

19

97

01

19

98

01

19

99

01

20

00

01

20

01

01

20

02

01

20

03

01

20

04

01

20

05

01

20

06

01

20

07

01

20

08

01

Standard repeat sales

Case-Shiller

Age-adjusted RS

Hedonic

Rolling hedonic


2 years


2014/11/18 page.

The Selection of Data Sources for the Construction of

Housing Price Indexes: Mick Silver (2014).

• Are house prices different depending on the stages of the

buying/selling process?

• We address this question by comparing the distributions of

prices collected at different stages of the buying/selling

process, including:

• (1) initial asking prices listed on a magazine or website,

• (2) asking prices at which an offer is made by a buyer,

• (3) contract prices reported by realtors after mortgage

approval,

• (4) contract prices from registry prices.



2014/11/18 page.

Price distributions : Price densities for P1, P2, P3, and P4

13

0.00

0.05

0.10

0.15

0.20

0.25

4.5

0

4.7

5

5.0

0

5.2

5

5.5

0

5.7

5

6.0

0

6.2

5

6.5

0

6.7

5

7.0

0

7.2

5

7.5

0

7.7

5

8.0

0

8.2

5

8.5

0

8.7

5

9.0

0

9.2

5

9.5

0

9.7

5

10

.00

10

.25

10

.50

P1

P2

P3

P4

log P


The distribution of transaction prices, P3 and P4 differs substantially

from that of asking prices, P1 and P2.


2014/11/18 page.

House purchase timeline

14

House placed on market

Offer made

Asking price in magazine

dataset (P1)

Final asking price in

magazine dataset (P2)

Mortgage approved

Contracts exchanged

Completion of sale with

Land Registry or REINS

Transaction price in realtor dataset (P3)

Transaction registered with

Land Registry

Transaction price survey

based on Land Registry Transaction price in

registry dataset (P4)

Timing of events in real estate

transaction process

Real estate price information

10 weeks

15.5 weeks

5.5 weeks


There is a time lag

around 30 weeks,

between P1 and P4.


2014/11/18 page.

Fluctuations in the price ratio and the interval for P1 and P2

15

35

40

45

50

55

60

65

70

75

80 0.950

0.955

0.960

0.965

0.970

0.975

0.980

0.985

0.990

0.995

20

05

07

20

05

10

20

06

01

20

06

04

20

06

07

20

06

10

20

07

01

20

07

04

20

07

07

20

07

10

20

08

01

20

08

04

20

08

07

20

08

10

20

09

01

20

09

04

20

09

07

20

09

10

Inte

rval

[d

ays]

Pri

ce r

atio

Price ratio (Left scale)

Interval (Right scale, Inverted)

0.00

0.05

0.10

0.15

0.20

0.25

20

05

07

20

05

10

20

06

01

20

06

04

20

06

07

20

06

10

20

07

01

20

07

04

20

07

07

20

07

10

20

08

01

20

08

04

20

08

07

20

08

10

20

09

01

20

09

04

20

09

07

20

09

10

Hedonic index for P1

Hedonic index for P2



2014/11/18 page.

3. Overall conclusions: Lessons from Shiller and Silver

• Q1: How do property prices affect the economic system or the

financial system?

• →Robert Shiller (2014)

• Q2: Do the different methods lead to different estimates of

property price changes? If the methods do generate different

results, which method should be chosen.

• Q3: Which data source should be used for property price

indexes?

• →Mick Silver (2014) & Robert Shiller (1987, 1989)



2014/11/18 page. 17

Hedonic indexes estimated using repeat-sales samples



2014/11/18 page.

Densities for relative prices

18

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

[0.6

5, 0

.70)

[0.7

0, 0

.75)

[0.7

5, 0

.80)

[0.8

0, 0

.85)

[0.8

5, 0

.90)

[0.9

0, 0

.95)

[0.9

5, 1

.00)

[1.0

0, 1

.05)

[1.0

5, 1

.10)

[1.1

0, 1

.15)

[1.1

5, 1

.20)

[1.2

0, 1

.25)

[1.2

5, 1

.30)

[1.3

0, 1

.35)

[1.3

5, 1

.40)

[1.4

0, 1

.45)

[1.4

5, 1

.50)

P1/P4

P2/P4

P3/P4


Documents

Real Estate Prices Availability, Importance, and New ......2014/11/18 · Second IMF Statistical Forum 2014 (IMF, Washington DC, US) 2014/11/18 page. 1. Macroeconomic Policy and Housing